Impact of tumor burden on survival in patients with recurrent or metastatic head and neck cancer treated with immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have become the standard treatment for recurrent or metastatic head and neck cancer (RM-HNC). However, many patients fail to benefit from the treatment. Previous studies have revealed that tumor burden predicts the efficacy of ICIs, but this association remains unclear for RM-HNC. We retrospectively analyzed 94 patients with RM-HNC treated with ICI monotherapy. We estimated the tumor burden using the baseline number of metastatic lesions (BNML) and the baseline sum of the longest diameters of the target lesions (BSLD), and evaluated the association between BNML, BSLD, and standardized uptake value (SUV) and clinical outcomes. The median progression-free survival (PFS) was 7.1 and 3.1 months in the low-BNML and high-BNML groups, respectively (p = 0.010). The median PFS was 9.1 and 3.5 months in the low-BSLD and high-BSLD groups, respectively (p = 0.004). Moreover, patients with high SUVmax levels had worse overall survival (OS) and PFS. BNML, BSLD, and SUVmax are useful prognostic factors in patients with RM-HNC treated with ICIs. Imaging examinations before ICI treatment are recommended to predict the efficacy of ICIs. If the tumor burden is high, cytotoxic anticancer agents may be administered concomitantly with or prior to ICI monotherapy.


Discussion
In the present study, we evaluated the impact of BNML, BSLD, and SUVmax on clinical outcomes in patients with RM-HNC treated with ICIs; the analyses identified high BNML, high BSLD, and high SUVmax as risk factors for worse survival rates and worse disease control rates.
To the best of our knowledge, this is the first study to clarify that high BNML, high BSLD, and high SUVmax are associated with worse clinical outcomes in patients with RM-HNC treated with nivolumab or pembrolizumab. A study suggested that pretreatment tumor size may affect response to nivolumab in patients with head and neck squamous cell carcinoma 10 ; but, we analyzed about both tumor size and number of lesions, as well as both nivolumab and pembrolizumab, to evaluate the impact of tumor burden on the clinical outcomes of ICIs.
The impact of tumor burden on survival has been reported for several cancers 9,11,12 . Miyawaki et al. reported that tumor burden can predict the efficacy of PD-1/PD-L1 inhibitor monotherapy against non-small cell lung cancer 9 . In this study, the values of BNML and BSLD were commonly available in clinical settings and were strongly associated with the clinical outcomes of PD-1/PD-L1 inhibitor monotherapy. Therefore, we adopted these parameters to evaluate tumor burden.
The mechanism by which a high tumor burden diminishes ICI efficacy remains unclear. Huang et al. demonstrated that a lower proportion of reinvigorated CD8 + T cells and tumor burden was associated with worse clinical outcomes in patients with melanoma treated with anti-PD-1 therapy 13 . Immune phenotypes of immuneinflamed, immune-excluded, and immune-deserted tumors have been described to be correlated with response to immunotherapy 14 . Therefore, the infiltration of immune cells may be regulated by a large tumor volume. However, tumor volume failed to correlate with immune phenotypes in one study 15 ; thus, further investigation is needed.
We also evaluated the impact of SUVmax on clinical outcomes. In other cancers, SUVmax has been reported as a prognostic factor or predictor in patients treated with ICIs 16,17 . Ichiki et al. demonstrated that aggressive cancers, such as those with high SUVmax, may not be suitable for ICIs 16 . Approximately 50% of patients in the present study were not included in the SUVmax analysis, but the results indicate an association between SUVmax and clinical outcomes in patients with RM-HNC treated with ICIs.
This study has several strengths. First, the number of patients who received anti-PD-1 monotherapy and were included in the study (n = 94) was relatively large. We found statistically significant differences in clinical www.nature.com/scientificreports/ outcomes between the high and low tumor burden groups. Second, we used both BNML and BSLD to evaluate the tumor burden. The BSLD is a useful marker, but unmeasurable lesions could not be evaluated. Therefore, we used both BNML and BSLD to minimize the potential variation from the actual tumor burden. Third, we evaluated the impact of SUVmax. The analysis suggests the potential use of SUVmax as a marker for predicting ICI efficacy. As a high SUVmax value may indicate tumor aggressiveness, SUVmax is a potential tool for evaluating tumor burden. This study has some limitations. First, it was a retrospective study conducted at a single institution. Second, we could not evaluate all metastatic lesions. The unmeasurable lesions, such as those with unclear borders or small lesions, were excluded from analyses. Third, the follow-up duration was too modest to evaluate long-term survival outcomes. Forth, although we analyzed both survival outcomes and the best overall response, it is difficult to strictly define the tumor burden as a predictive factor or prognostic factor for ICI treatment, because this is not a comparison study between ICIs and other treatment 18 . Therefore, a prospective, multicenter study is warranted to evaluate the impact of clinical tumor burden on survival in patients with RM-HNC treated with ICIs.
In conclusion, the study suggests that BNML, BSLD, and SUVmax may be prognostic factors in patients with RM-HNC treated with nivolumab or pembrolizumab monotherapy. We recommend to perform imaging examinations, including computed tomography (CT), magnetic resonance imaging (MRI), and PET before administration of ICIs to assess tumor spread and predict efficacy of ICIs. The study also indicates that a high tumor burden may qualify for chemotherapy with cytotoxic agents to be administered with or prior to ICI monotherapy.

Methods
Patients. We retrospectively analyzed 94 patients with RM-HNC who received nivolumab or pembrolizumab monotherapy at the Nagoya City University Hospital between July 2017 and September 2021.
We defined measurable tumor lesions as those with the longest diameter > 10 mm on CT or MRI. Measurable neck lymph nodes were defined as those with maximum minor axis diameter > 10 mm. We estimated the tumor burden using BNML and BSLD 9 . We defined BNML as both measurable and unmeasurable lesions, and multiple metastases in the same region were counted as single lesions.
We also measured SUVmax using PET and assessed its impact on survival. Patients who did not undergo PET in the duration between the appearance of recurrent/metastatic lesions and initial administration of nivolumab or pembrolizumab were excluded from analyses of SUVmax.
Treatment and follow-up. Between July 2017 and January 2020, nivolumab was administered at a dosage of 3 mg/kg every two weeks. Between February 2020 and April 2021, the dosage was 240 mg/body every two weeks. In stable cases, nivolumab was administered at a dosage of 480 mg/body every four weeks since September 2020. Pembrolizumab was administered at a dosage of 200 mg/body every three weeks in standard cases and 400 mg/body every six weeks in stable cases. The response to these therapies was evaluated according to the Response Evaluation Criteria in Solid Tumor (RECIST) version 1.1 19 , using CT or MRI, every 8-12 weeks. Patients with clinically obvious disease progression were diagnosed with PD even when images were not evaluated. Chemotherapy with cytotoxic agents was administered to patients diagnosed with PD. Follow-up was continued until death or the cutoff date (November 30, 2021).   www.nature.com/scientificreports/ death from any cause. The median OS and PFS were evaluated using the Kaplan-Meier method and log-rank test. The impact of BNML, BSLD, and SUVmax on survival was assessed using univariate and multivariate analyses with Cox proportional hazards models. The cutoff value for each factor was determined by performing ROC curve analyses. The correlations between BNML, BSLD, and response to anti-PD-1 monotherapy were assessed using univariate and multivariate logistic regression analyses. A p < 0.05 was considered to be statistically significant. Age, sex, ECOG PS, and BOR for anti-PD-1 antibody monotherapy were defined as potential confounders in multivariate analysis of OS. Whereas, age, sex, and ECOG PS were defined as confounders in multivariate analysis of PFS. All analyses were performed using EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan), a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria, version 3.5.0). EZR, a modified version of the R commander (version 2.7-1), was designed to incorporate statistical functions frequently used in biostatistics.

Ethical approval. This study was approved by the Institutional Review Board of the Nagoya City University
Graduate School of Medical Sciences (Accession No. 60-21-0001). As this was a retrospective, non-intervention study, patients could reject participation by opting out to an announcement on the Nagoya City University Hospital's website, and the requirement of written informed consent was waived. This study was conducted in accordance with the principles of the Declaration of Helsinki.

Data availability
The datasets generated and/or analyzed during the study are available from the corresponding author upon reasonable request. Table 2. The association between the tumor burden and clinical outcomes in patients with recurrent or metastatic head and neck cancer treated with immune checkpoint inhibitors. Adjusted by age, sex, Eastern Cooperative Oncology Group performance status. In analysis for overall survival, adjusted also by best overall response for anti-PD-1 monotherapy. HR hazard ratio, CI confidence interval, BNML the baseline number of metastatic lesions, BSLD the baseline sum of the longest diameters of the target lesions, SUV standardized uptake value.  www.nature.com/scientificreports/ Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.